The Prevalence of Cannabis Use Disorder in Individuals with Anxiety or Related Disorders: A Systematic Review
Bibliographic record
Abstract
Objective The current study aimed to systematically review the prevalence of comorbid Cannabis Use Disorder (CUD) in individuals with Anxiety and Related Disorders (ARDs).Method PubMed, PsycInfo, and Web of Science were searched electronically to identify studies comprised of participants 18+ years, diagnosed with a current ARD via clinician interview and experiencing comorbid CUD (interview or validated screener). Of the 1646 articles identified, 11 were included.Results Across general population samples (n = 7), approximately 1 in 30 to 1 in 5 individuals with an ARD had comorbid CUD (lifetime prevalence: 3.3%–21.6%; current prevalence: 4.3%–20.0%). Among veteran samples with PTSD (n = 4), comorbid CUD was reported in approximately 1 in 25 to 1 in 3 individuals for current prevalence (4.1%–34.0%), and about 1 in 9 for lifetime prevalence (11.3%–12.5%).Conclusion Preliminary evidence suggests that individuals with ARDs may be susceptible to developing comorbid CUD. Current comorbidity rates may be higher among veterans with PTSD compared to adults in general population samples; however, due to the limited number of eligible studies and methodological heterogeneity, further research is needed to confirm this difference. Given the recent global increase in cannabis legalization, understanding ARD–CUD comorbidity in high-risk populations is essential to inform treatment and improve outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".